AI-POWERED CHAT BOT FOR MENTAL HEALTH

OBIEFUNA, JUDITH UCHECHI (2025) AI-POWERED CHAT BOT FOR MENTAL HEALTH. Other thesis, GODFREY OKOYE UNIVERSITY, ENUGU.

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Abstract

This paper outlines the proposal of an AI-based mental encounter examination chatbot that would convey scaleable and time-unbiased psychological assistance that is aware of its circumstance. The system uses the best of Natural Language Processing (NLP) such as intent classification and sentiment analysis to see meaning in what the user type in and use that to come up with a response that is in context. The chatbot is implemented on a hybrid architecture that integrates rule-based logic with machine-learning models allowing the chatbot to recognize cues of emotional distress as well as distinguish between common or relatively high-level information and crisis-level input and respond with evidence-based intervention or escalation procedures. Its salient characteristics are individual interaction history, adaptive course of conversation, and privacy-focused data management framework that would guarantee observation of ethical standards and data protection laws. In comparison with the current solutions, the proposed chatbot will be more personalized, will recognize crises more accurately, and will be more flexible to vary user situations. The system should be used to supplement the traditional services of mental health by offering continuous/around the clock support, thus filling the gaps in services and offloading healthcare professionals. And this Chabot can locate the nearest clinic or hospital for advance treatment using goggle location map. The proposed chatbot will implement object- oriented analysis and design for both analysis and design of the system. The tools include goggle map API, health care chat bot API, java script, html and CSS.

Item Type: Thesis (Other)
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Natural and Applied Sciences
Depositing User: Uchenna Eneogwe
Date Deposited: 05 Jun 2026 10:31
Last Modified: 05 Jun 2026 10:31
URI: http://eprints.gouni.edu.ng/id/eprint/5757

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